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cs.RO2026
Provably Safe Motion Planning Under Unknown Disturbances
Ibon Gracia, Qi Heng Ho, Luca Laurenti +1
We present a provably safe sampling-based motion planning algorithm for robotic systems affected by random disturbances of unknown distribution. We consider systems with linear or…
eess.SY2026
On the Optimality of Uncertain MDP Abstractions
Ibon Gracia, Morteza Lahijanian
We study the asymptotic optimality of abstraction-based control synthesis algorithms. Specifically, we consider uncertain MDP (UMDP) abstraction, and investigate whether refinement…
eess.SY2026
Training with Hard Constraints: Learning Neural Certificates and Controllers for SDEs
Chun-Wei Kong, Sebastian Escobar, Ibon Gracia +2
Due to their expressive power, neural networks (NNs) are promising templates for functional optimization problems, particularly for reach-avoid certificate generation for systems g…